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ai data engineer

<div>
 <p>
  <strong>
   Role: Senior Data Analytics Engineer with AI Initiatives (Must)
  </strong>
 </p>
 <p>
  <strong>
   Location: New York/ Remote
  </strong>
 </p>
 <p>
  <strong>
   Experience: 5 - 10 years
  </strong>
 </p>
 <p>
  <strong>
   Duration: Full time
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Description:
  </strong>
 </p>
 <p>
  We are looking for a Lead Engineer to build and maintain scalable data pipelines and data platforms that support analytics, business Intelligence, reporting, and AI initiatives. In this role, you will work closely with data architects, analysts, and business stakeholders to develop reliable data solutions and ensure high-quality data is available across the organization.
 </p>
 <p>
  This is a
  <strong>
   hands-on engineering role
  </strong>
  focused on designing efficient data pipelines, improving data infrastructure, and enabling teams to leverage data effectively.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design, build, and maintain scalable
   <strong>
    data pipelines and ETL/ELT workflows
   </strong>
   to ingest and transform data from multiple sources
  </li>
  <li>
   Develop and optimize
   <strong>
    batch and near real-time data processing pipelines
   </strong>
   for analytics and reporting
  </li>
  <li>
   Build and maintain
   <strong>
    data warehouse and data lake structures
   </strong>
   to support business intelligence and analytics use cases
  </li>
  <li>
   Implement and maintain
   <strong>
    data models
   </strong>
   that support efficient querying and reporting
  </li>
  <li>
   Improve performance and scalability of data systems through
   <strong>
    query optimization, indexing, and partitioning strategies
   </strong>
  </li>
  <li>
   Implement
   <strong>
    data quality checks, monitoring, and logging
   </strong>
   to ensure reliability of data pipelines
  </li>
  <li>
   Exposure to
   <strong>
    AI initiatives
   </strong>
   and experience
   <strong>
    building data pipelines
   </strong>
   supporting
   <strong>
    AI workflows
   </strong>
  </li>
  <li>
   Work with data architects and engineering teams to implement
   <strong>
    scalable data platform designs
   </strong>
  </li>
  <li>
   Collaborate with analysts, BI developers, and business stakeholders to deliver data solutions that support business needs
  </li>
  <li>
   Maintain documentation for data pipelines, data models, and data workflows
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    5 - 10 years of experience
   </strong>
   in Data Engineering and GenAI and Data Scientist and AI Engineer
  </li>
  <li>
   Strong experience with
   <strong>
    SQL and Python
   </strong>
   for data processing and transformation
  </li>
  <li>
   Experience building and maintaining
   <strong>
    ETL/ELT pipelines
   </strong>
  </li>
  <li>
   Solid understanding of
   <strong>
    data warehousing concepts and dimensional data modeling
   </strong>
  </li>
  <li>
   Experience working with
   <strong>
    cloud data platforms or modern data infrastructure
   </strong>
  </li>
  <li>
   Familiarity with
   <strong>
    workflow orchestration tools
   </strong>
   such as
   <strong>
    Airflow
   </strong>
   or similar
  </li>
  <li>
   Understanding of
   <strong>
    API-based data ingestion and data integration patterns
   </strong>
  </li>
  <li>
   Strong problem-solving and collaboration skills
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Education
  </strong>
 </p>
 <p>
  Bachelor's or master's degree in computer science
  <strong>
   , Engineering, Information Systems, or a related field
  </strong>
  , or equivalent practical experience.
 </p>
</div>


AI Data Engineer

Locality

<div><p>Locality is seeking a Senior Data Engineer whom will serve as the primary internal owner of our Audience Engine, spanning data ingestion, identity resolution, automation, and AI enablement. This role emphasizes hands on platform stewardship today, with a clear path to supporting future expansion of the HH Identity Graph and applied AI use cases.
</p><ul><li>Establish and own technical management of the Audience Engine, transitioning knowledge from external partners and building a scalable, internally managed data platform</li><li>
Reduce reliance on third-party vendors while maintaining high standards for platform reliability, uptime, and data integrity across all pipelines and integrations</li>
Architect, own, and continuously optimize Databricks Bronze Silver<li> Gold pipelines to support large scale audience ingestion, enrichment, and activation workflows</li><li>
Ensure the platform is scalable and cost efficient through effective pipeline optimization and resource management</li><li>
Proactively monitor, troubleshoot, and resolve ingestion failures, schema drift, and data quality issues across batch and near real time data pipelines</li><li>
Lead identity resolution across datasets including HHID, DSID, MAID, IP, and campaign logs, improving matching logic to strengthen the Household Identity Graph</li><li>
Guarantee accurate and timely audience publication by maintaining robust downstream data delivery processes and SLAs across activation platforms and partners</li><li>
Own and maintain integrations with external data and activation partners (e.g., Experian, FreeWheel, DSPs), ensuring seamless data exchange and operational reliability</li><li>
Partner cross functionally with Product, Analytics, and Ad Operations teams to onboard new data sources and activation endpoints, enabling new use cases and revenue opportunities</li><li>
Support and operationalize applied AI/ML workflows within Databricks, including integration with tools like Akkio, and translate business needs into production-ready data features and datasets</li><li>
Design and implement scalable data models and query-ready datasets that power BI reporting, audience insights, and predictive modeling, ensuring alignment with downstream analytics requirements</li><li>
Enforce data governance, lineage, and documentation standards while ensuring compliance with privacy, consent, and data usage regulations across all audience and identity data systems</li></ul><ul><li>
6+ years of experience as a Data Engineer or Data Platform Engineer, ideally within advertising</li><li>
Strong hands on experience with Databricks, Spark, and modern cloud data platforms</li><li>
Proven experience designing and maintaining multi-layered data architectures (Bronze / Silver / Gold)</li><li>
Deep expertise in SQL and proficiency in Python or another scripting language</li><li>
Experience working with identity graphs, audience data, and complex join logic across large datasets</li><li>
Hands on experience building and managing automated data pipelines and third-party data integrations</li><li>
Familiarity with adtech, martech, or audience activation platforms, including exposure to identity providers such as Experian or similar vendors</li><li>
Practical experience supporting AI/ML workflows or AI-enabled analytics, with an understanding of data quality, schema design, and performance optimization in cloud-scale environments</li></ul><p>
</p><p><i>Compensation for the role includes a competitive base salary in the range from $75-$100/hr (dependent on years of experience, level of education obtained, as well as applicable skillset), and an excellent benefits package (including but not limited to health care benefits, retirement benefits and paid days off).
</i></p><p></p><p><i>At Locality, we believe our biggest asset is our people. We are proud to be an equal opportunity employer, hiring and developing individuals from diverse backgrounds and experiences to add to our collaborative culture. Locality values and solicits applications from all qualified candidates without regard to actual or perceived race, creed, color, religion, sex, gender, age, physical or mental disability, medical condition, sexual orientation, gender identity and/or expression, alienage or national origin, ancestry, citizenship status, marital status, military or veteran status, genetic information, or any other basis protected by federal, state, or local law.</i></p></div>

Sr. Data Engineer (Contract to Perm)

Data Engineer, Product Analytics

Edra

<div>
 <strong>
  About Edra
  <br/>
  <br/>
 </strong>
 Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations.
 <br/>
 <br/>
 We're a Series A startup, backed by Sequoia and other leading VC firms, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build.
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 We're looking for Full Stack Engineers who care deeply about the craft of building software: strong typing, thoughtful API design, robust data modeling, and interfaces that are a pleasure for both users and other engineers to work with. You won't be building AI models&ndash;you'll be building everything around them: the platform, workflows, user-facing experiences, integrations, and observability that make our AI useful in the real world. As an early engineer at Edra, you'll shape not just the product but the engineering culture, tooling choices, and technical foundations the company is built on.
 <br/>
 <br/>
 We work deliberately and deeply. There's no separation between "building it" and "shipping it"--you'll go from whiteboard to production and own the outcome. We'd rather build something thoughtfully than ship something fragile, and we treat velocity and quality as complementary, not competing.
 <br/>
 <br/>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and build platform systems in Python (FastAPI)--from API contracts to database schema and infrastructure&ndash;and high-quality user-facing experiences in TypeScript and React, with an emphasis on clean component design, strong typing, and maintainable frontends
  </li>
  <li>
   Build shared TypeScript and Python libraries, component systems, and internal tooling that make the rest of the engineering team more productive. Define and enforce patterns, shared types, and contracts across the frontend and API boundary
  </li>
  <li>
   Own your work fully: gather context, manage dependencies, and drive tasks to completion without a product manager handing you tickets. You might design a schema in the morning, build a React component in the afternoon, and debug a deployment issue before end of day
  </li>
  <li>
   Contribute to the direction and design of our product. Work closely with design, reason clearly about interface decisions, and participate in weekly product meetings to understand how customers and forward-deployed engineers use what you build
  </li>
  <li>
   Build and maintain connectors, integrations, and data pipelines that connect our platform to external systems
  </li>
  <li>
   Have direct influence on technical direction; choose tools, set patterns, and establish conventions the team will build on for years. Collaborate daily with a small, high-caliber team of engineers and AI specialists
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We&rsquo;re Looking For
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3+ years of experience in software engineering (but a computer science degree is not necessarily required)
  </li>
  <li>
   A love of writing Python and TypeScript to a genuinely high standard&ndash;well-modeled, well-typed, and well-documented. Strong typing feels like a superpower, not a chore
  </li>
  <li>
   You light up when designing a clean database schema and take real pride in getting data models right
  </li>
  <li>
   You have good visual and interaction judgment, even if you're not a designer by title
  </li>
  <li>
   You've built libraries, SDKs, or internal tooling that made other developers' lives easier (and you&rsquo;ve enjoyed it)
  </li>
  <li>
   You're at your best when you own a problem end to end&ndash;comfortable with ambiguity and energized by turning a vague problem into a well-scoped solution
  </li>
  <li>
   You're drawn to building foundational systems from scratch&ndash;greenfield work where your decisions compound over time excites you
   <br/>
   <br/>
  </li>
 </ul>
 Don't meet all of the above? We'd still love to hear from you. We're looking for exceptional people with unique skills and interests, and we know that great people have different backgrounds and skillsets. If your primary interest is building agentic systems, working with LLMs, or doing applied ML, check out our AI Engineering role&ndash;it might be a better fit.
 <br/>
 <br/>
 <strong>
  Learn More About Edra
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Watch our Series A announcement video
  </li>
  <li>
   Read our blog post from our launch
  </li>
  <li>
   Learn more about what we're building
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  A Few Details
  <br/>
  <br/>
 </strong>
 Edra is an equal opportunity employer and we encourage applications from individuals of all backgrounds. Edra does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital status, sexual orientation, gender identity, veteran status, or any other legally protected characteristic.
 <br/>
 <br/>
 Compensation Range: $180K - $250K
 <br/>
 <br/>
</div>


Software Engineer - Full Stack (New York)

Giga

<div>
 <strong>
  About Giga
  <br/>
  <br/>
 </strong>
 Giga has recently raised a $61M Series A and has several paying customers, including DoorDash. We&rsquo;re building the next generation of customer experience &mdash; real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world&rsquo;s largest enterprises.
 <br/>
 <br/>
 It&rsquo;s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers.
 <br/>
 <br/>
 The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us:
 <br/>
 <br/>
 <ul>
  <li>
   Voice AI startup Giga raises $61M Series A
  </li>
  <li>
   DoorDash and Giga Partnership
   <br/>
   <br/>
  </li>
 </ul>
 Giga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply!
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 We're looking for software engineers to help build the systems that power our AI agents. You'll work across the backend, from data pipelines and integrations to agent infrastructure, shipping features alongside experienced engineers who will help you grow.
 <br/>
 <br/>
 This is a role where you'll contribute to real problems from day one. We expect you to ramp up quickly, take ownership of your work, and operate with increasing independence as you learn the codebase.
 <br/>
 <br/>
 <strong>
  What You'll Work On
  <br/>
  <br/>
 </strong>
 You'll contribute to projects across our stack. Some examples:
 <br/>
 <br/>
 <ul>
  <li>
   Atlas: Building features for our AI assistant: charts and alerts in Slack, natural language queries, and expanding Atlas to manage platform resources
  </li>
  <li>
   Activity Stream: Log visualization with filters, timestamps, and frequency charts to give visibility into agent behavior
  </li>
  <li>
   Dynamic knowledge: Adding time-based knowledge (like ongoing incidents) that auto-updates from sources like status pages
  </li>
  <li>
   Agent memory: Conversation awareness and recent interaction lookups so agents remember context across sessions
   <br/>
   <br/>
  </li>
 </ul>
 As an early-career engineer, you'll be paired with senior engineers on larger initiatives while also owning smaller projects end-to-end as you ramp up.
 <br/>
 <br/>
 <strong>
  You Might Be a Fit If You
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have 1-3 years of professional software engineering experience
  </li>
  <li>
   Are curious and ask good questions&mdash;you want to understand why things work, not just how
  </li>
  <li>
   Can take feedback well and iterate quickly
  </li>
  <li>
   Prefer shipping over perfection but still care about quality
  </li>
  <li>
   Want to grow at a startup where you'll have real responsibility early
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Perks &amp; Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Catered lunch daily
  </li>
  <li>
   Dinner stipend
  </li>
  <li>
   $150/month wellness benefit (gym, fitness classes, mental health)
  </li>
  <li>
   401(k) plan
  </li>
  <li>
   Paid parental leave (12 weeks maternal, 6 weeks paternal)
  </li>
  <li>
   Commuter benefits
  </li>
  <li>
   Medical, dental, and vision coverage
   <br/>
   <br/>
  </li>
 </ul>
 Giga is an equal opportunity employer. We're committed to providing equal employment opportunities regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.
 <br/>
 <br/>
 Compensation Range: $160K - $250K
 <br/>
 <br/>
</div>


Software Engineer I / II - New York

Middesk

<div>
 <strong>
  About Middesk
  <br/>
  <br/>
 </strong>
 Middesk makes it easier for businesses to work together. Since 2018, we&rsquo;ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle.
 <br/>
 <br/>
 Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List.
 <br/>
 <br/>
 <strong>
  The Role:
  <br/>
  <br/>
 </strong>
 We&rsquo;re building AI-driven applications that power business onboarding, fraud prevention, and identity verification. With proprietary data assets and deep domain expertise, we&rsquo;re uniquely positioned to create a new generation of ML-powered solutions for trust and risk.
 <br/>
 <br/>
 We&rsquo;re looking for a
 <strong>
  hands-on Machine Learning Engineer with strong Data Science expertise
 </strong>
 to take end-to-end ownership of the ML lifecycle: from feature design and model development, to deployment, monitoring, and iteration in production. Unlike larger organizations where responsibilities are split, you&rsquo;ll have the opportunity to
 <strong>
  own models from concept to production
 </strong>
 while working closely with product managers, engineers, and data platform teammates who support and amplify your work.
 <br/>
 <br/>
 This is a rare chance to join an
 <strong>
  earlier-stage company
 </strong>
 where you&rsquo;ll have broad visibility and influence, and where your ML systems will have immediate and measurable impact on customers.
 <br/>
 <br/>
 What You&rsquo;ll Do:
 <br/>
 <br/>
 <ul>
  <li>
   End-to-end ML ownership: Lead the full lifecycle of ML systems &mdash; feature engineering, model design, training, evaluation, deployment, monitoring, and iteration.
  </li>
  <li>
   Collaborate with a strong team: Work alongside data engineers, platform engineers, and product teammates who ensure you have the infrastructure, data, and context to deliver.
  </li>
  <li>
   Design &amp; deploy production models: Build high-performance ML applications in risk, fraud, trust &amp; safety, and compliance domains.
  </li>
  <li>
   Keep models healthy in production: Proactively monitor, detect drift, and retrain to ensure long-term performance and reliability.
  </li>
  <li>
   Experiment &amp; learn: Drive online experiments, offline evaluation, and counterfactual analyses to prove impact.
  </li>
  <li>
   Shape ML foundations: Contribute to the feature store, model management, training/serving pipelines, and best practices that scale ML across multiple use cases.
   <br/>
   <br/>
  </li>
 </ul>
 What We&rsquo;re Looking For:
 <br/>
 <br/>
 <ul>
  <li>
   4+ years applied ML experience with proven impact in risk, fraud, trust &amp; safety, compliance, fintech, or other high-stakes domains.
  </li>
  <li>
   Track record of owning ML models end-to-end &mdash; from research and design to deployment, monitoring, and retraining in production.
  </li>
  <li>
   Strong software engineering skills (Python, ML frameworks, deployment pipelines) and ability to write reliable, production-grade code.
  </li>
  <li>
   Hands-on experience with ML infrastructure such as feature stores, model management, training/serving pipelines, and monitoring tools.
  </li>
  <li>
   Comfortable as a senior IC: you can set technical direction, establish best practices, and mentor peers while collaborating effectively across teams.
  </li>
  <li>
   Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML systems to life.
  </li>
  <li>
   Deep expertise in classification challenges such as imbalanced labels, sparse signals, cold start, and production version management.
   <br/>
   <br/>
  </li>
 </ul>
 Nice to Haves:
 <br/>
 <br/>
 <ul>
  <li>
   B2B SaaS experience, ideally building ML products for enterprise customers.
  </li>
  <li>
   Familiarity with graph, LLM-based feature generation, or AI agent workflows.
  </li>
  <li>
   Experience scaling ML across multiple products or risk domains.
  </li>
 </ul>
</div>


Machine Learning Engineer

COMPLEX

<div><div><b>Company And Culture</b></div>
<div></div>
<div>Complex is the definitive platform for global youth culture and music lifestyle, seamlessly integrating cutting-edge content, commerce and live experiences with unparalleled scale. Through innovative content, Complex tells stories of music, streetwear and style, sports, art and beyond. Its content engages in a dynamic conversation with the audience, reflecting and shaping the zeitgeist of convergence culture. A powerful media juggernaut paired with a curated marketplace, Complex is redefining the way fans interact with their favorite brands and artists and reshaping the future of digital culture and commerce.</div>
<div></div>
<div><b>Why We're Hiring
</b></div>
<div></div><div>Complex operates at the intersection of content, commerce, and culture&mdash;powering media, live experiences, marketplace, and audience engagement across sneakers, music, sports, and streetwear. This ecosystem generates a high volume of workflows, audience intelligence, and creative output. Much of that operational value, however, remains fragmented across SaaS platforms, manual processes, and institutional knowledge. We are building the next layer of infrastructure to change that.
</div>
<div></div><div>The AI Orchestra Director: Agentic Infrastructure Engineer will embed directly within our technology organization, ensuring that every architectural decision drives measurable business outcomes. The role bridges system design, implementation, and operational impact. Complex is seeking an AI Orchestra Director&mdash;a hands-on technical architect and builder responsible for designing, deploying, and operationalizing our agentic AI infrastructure. This is not an advisory position. It is an execution-driven engineering mandate to build a parallel infrastructure layer that enables AI agents to:</div>
<ul><li>Automate core workflows</li></ul>
<ul><li>Replace high-cost SaaS platforms with owned solutions</li></ul>
<ul><li>Modernize data access and experimentation</li></ul>
<ul><li>Generate proprietary, reusable intellectual property</li></ul>
<ul><li>All while the business continues to operate without disruption</li></ul>
<div></div>
<div><b>Work Schedule:</b></div>
<div>Possible freelance to hire, 4-6 month project Monday - Friday</div>
<h3 class="jobSectionHeader"><b>What You'll Do</b></h3><ul>
<li><b>Top Three Strategic Priorities:</b></li>
<li>1. Architect and Deploy the Agentic Infrastructure Layer</li>
<li>Design and implement a scalable runtime environment purpose-built for a media and commerce organization, including:</li>
<li>Agent orchestration and task routing</li>
<li>Quality gates and human-in-the-loop checkpoints</li>
<li>Logging, observability, and convergence tracking</li>
<li>CI/CD and deployment pipelines</li>
<li>On-premise or hybrid environment architecture</li>
<li>This foundation must be secure, extensible, and maintainable by the existing engineering team</li>
</ul>
<div></div><ul><li>2. Lead the Tool Replacement Program</li>
<li>Audit current SaaS licenses and identify high-cost, high-leverage replacement opportunities (e.g., CRM, analytics, workflow tools)</li>
<li>Using agentic development practices:</li>
<li>Build internal tools with AI agents writing and testing code</li>
<li>Maintain human review at critical checkpoints</li>
<li>Deliver measurable license cost reductions</li>
<li>Demonstrate infrastructure ROI within the engagement period</li>
<li>The objective: prove the system&rsquo;s value by using agents to build the tools themselves</li>
</ul>
<div></div><ul><li>3. Codify Operational Workflows into a Reusable Skills Library</li>
<li>Partner across departments to:</li>
<li>Identify and document high-impact operational workflows</li>
<li>Encode them into version-controlled, reusable agent &ldquo;skills&rdquo;</li>
<li>Transform tribal knowledge into durable company-owned IP</li>
<li>The result: a scalable library of automated capabilities that can operate independently of the engagement</li>
</ul>
<div></div><ul><li><b>Key Responsibilities:</b></li>
<li>Architect and deploy the agentic infrastructure layer in collaboration with executive leadership and the Platform Studio engineering team</li>
<li>Design a modern, growth-oriented data access layer built on existing Snowflake infrastructure and related data sources</li>
<li>Enable agent-native querying, rapid experimentation, and insight generation</li>
<li>Evaluate and integrate open-source orchestration tools to maintain vendor-agnostic flexibility</li>
<li>Implement test-driven development enforcement, intelligent retry logic, and convergence tracking</li>
<li>Establish governance frameworks with human-in-the-loop checkpoints for production deployment and auditability</li>
<li>Embed seamlessly with existing engineering teams&mdash;building trust, not parallel power structures</li>
<li>Develop documentation, training protocols, and knowledge-transfer systems to ensure long-term sustainability</li>
<li>Partner with the COO and department leaders to prioritize automation initiatives that simultaneously reduce cost and increase velocity</li>
<li>Foster a culture shift toward agentic development as a core capability within the organization</li>
</ul><h3 class="jobSectionHeader"><b>Who You Are</b></h3><ul>
<li>Proven experience building and deploying AI agent infrastructure in production environments</li>
<li>Deep proficiency across LLM orchestration frameworks, retrieval-augmented generation (RAG), prompt engineering, and agentic coding workflows</li>
<li>Strong systems architecture background with infrastructure designed for long-term maintainability</li>
<li>Experience with data engineering and analytics infrastructure (Snowflake and API-based systems preferred)</li>
<li>Comfort evaluating and integrating open-source tooling within a multi-model ecosystem (e.g., Claude, Codex, Gemini, open-source models)</li>
<li>Git-native workflow mindset (branches, PRs, CI/CD, TDD)</li>
<li>Exceptional ability to translate complex architecture into business-aligned outcomes</li>
<li>Experience embedding within existing teams and leaving them stronger than you found them</li>
<li>Media, entertainment, or commerce industry experience preferred but not required</li>
<li>Comfortable with whiteboarding systems with executive leadership</li>
<li>Creating shipping production-ready pipelines</li>
<li>Reviewing agent-generated code</li>
<li>Ability to train teams to extend what you&rsquo;ve built</li>
</ul>
<div></div><ul><li><b>Success Metrics (By the end of the 12 week engagement, you will have delivered):</b></li>
<li>A working agent runtime environment with orchestration, logging, quality gates, and CI/CD pipelines</li>
<li>At least two deployed internal SaaS replacements with documented cost savings</li>
<li>A versioned skills library containing a minimum of ten codified operational workflows</li>
<li>A defined and partially implemented data access layer serving both human users and AI agents</li>
<li>Complete knowledge transfer to the existing engineering team</li>
<li>Seamless organizational integration with no structural friction</li>
</ul>
<div></div><ul><li><b>What Success Looks Like:</b></li>
<li>Success is not measured solely by architectural elegance &ndash; It is measured by operational independence</li>
<li>Workflows that execute autonomously</li>
<li>Tools built internally rather than rented</li>
<li>Data systems that surface insights proactively</li>
<li>An engineering organization fluent in agentic development</li>
</ul><div>The Pay Range, which consists of salary and commission, for this position is listed. Actual pay will vary based on factors including, but not limited to location, experience, and performance. The range listed is just one component of Complex Total Rewards offerings for employees.</div><div>
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.</div>
<div></div>
<div><i>The above statements cover what are generally believed to be principal and essential functions of the job. Specific circumstances may allow or require some incumbents assigned to the job to perform a different combination of duties.</i></div>
<div></div>
<div><i>Complex participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.</i></div>
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<div><i>Candidates must be legally authorized to work in the U.S. without the need for visa sponsorship.</i></div></div>

Director, Agentic AI Infrastructure & Orchestration Engineer

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